Senior Agentic AI Architect

As Senior Agentic AI Architect & Developer you will architect, build, and implement advanced AI systems centered on Agentic AI. You will be working closely with cross-functional teams, align Agentic AI and Innovation strategies to business goals and deliver high-impact value. You'll mix deep technical mastery with an innovation-first mindset to turn ideas into production-grade solutions that drive efficiency and profitability while advancing the Enterprise Digital Transformation & Innovation agenda. This role sits at the heart of our new EMEA Agentic AI & Automations CoE within the EMEA Digital Workplace organization and reports to the EMEA DW Head of Innovation & Agentic AI

Main Responsibilities

• Develop Agentic AI and multi-agent architecture and systems for real business and clients use cases that balance modularity, scalability, and flexibility.
• Design and orchestrate multi-agent blueprints—including orchestration, tool use, memory, and human-in-the-loop — and apply them for rapid rollout across multiple client deployments (including conversational chat/voice workflows where appropriate).
• Establish standards and reusability by formalizing architecture and producing reusable components such as agent templates, planners, and memory stores.
• Architect robust Agentic AI frameworks and develop multi-agent systems from prototype to production.
• Productize and operate Agentic AI with lifecycle management on modern infrastructure such as Kubernetes and microservices. Leverage building blocks such as vector databases, agent-orchestration frameworks and RAG pipelines.
• Collaborate and align with product and operations teams to define agent behaviors and translate business needs into executable architecture and deployment blueprints.
• Ensure adherence to AI governance and enterprise risk frameworks.
• Monitor and optimize continuously by establishing evaluation loops for Agentic AI performance, safety, and compliance
• Support day-to-day operations of Agentic AI systems, troubleshoot agents issues, monitor system performance, and provide technical guidance to keep production environments healthy
• Support innovation initiatives - partner with internal and customer business stakeholders to identify high-impact use cases and accelerate digital transformation and process automation.
• Scan and apply the latest market capabilities in AI to unlock new opportunities for measurable improvement.
• Mentor engineers on agentic design principles, reusable patterns, testing strategies, and production hardening

Skills, Knowledge & Experience

• Hands-on (3+ years) building Agentic AI and automation solution Architecture, with proven successes in Agentic AI solutions.
• Hands-on expertise with Microsoft Azure AI services - particularly Azure AI Foundry, Azure AI Agent Service, Azure OpenAI, Azure ML, Cognitive Search, Azure AI Studio,Microsoft Copilot Studio, and Semantic Kernel.
• Expertise with Google Cloud AI offerings (Vertex AI, PaLM models, GCP RAG pipelines).
• Hands-on development and orchestration of AI agents using Python; multi-agent frameworks (LangChain, LangGraph, CrewAI, AutoGen); vector databases (FAISS, Pinecone, Weaviate); and RAG pipelines.
• Experience with other Agentic automation platforms such as N8N, Aisera (ideal), Kore.AI, Make, and Zapier.
• Strong experience identifying opportunities for automation and Digital Transformation with AI-based capabilities within enterprise environments.
• Working knowledge of cloud architectures (Azure - ideal, AWS, GCP), enterprise integration patterns, and DevOps practices.
• Strong understanding of reasoning and decision engines and functions
• Deep experience across the agentic development lifecycle—from initial concept and experimentation through pre-production assessment, production operations, and continuous improvement.
• Ability to identify, evaluate, test, and implement the most effective variations for agentic use cases, including building alternatives to Aisera workflows using Azure AI Foundry, Microsoft Copilot Studio, Power Platform or other to achieve optimal outcomes and costs.
• Strong software-engineering foundation with 5+ years designing and implementing complex software systems.
• Expert-level proficiency in Python and with modern JavaScript frameworks, plus practical experience with AI/ML libraries (PyTorch, TensorFlow, Hugging Face).
• Experience designing and implementing distributed systems, microservices architectures, and APIs (development and troubleshooting).
• Proven track record of deploying and managing production AI systems with monitoring, logging, and observability.
• Deep understanding of LLM evaluation metrics, fine-tuning techniques, and prompt engineering.
• Experience with containerization (Docker) and orchestration platforms (Kubernetes).
• Expertise in implementing robust CI/CD pipelines for AI applications.

Nice to have

• Prior knowledge of Power Platform.
• Knowledge of Model Context Protocol (MCP), Agent-to-Agent (A2A), and other agentic protocols.
• Experience with rapid prototyping of Generative and Agentic AI solutions.
• Familiarity with ITSM and Contact Center/Customer Service processes and industry.
• Experience with AI safety testing frameworks